Application of deep learning in cardiovascular medicine using multiple biomedical data

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Abstract

Today with the help of emerging technologies scientists can gather data in many sectors which includes the Healthcare sector. The amount of data generated by machines and humans is overwhelming and is growing faster than it has ever had before. Taking advantage of all the power that exist in that data we have come up with a novel idea where we have used the development of machine learning techniques in diagnosing cardiovascular disease. Here, we fit a function to examples and using the function to generalize and make predictions about new diagnosis. In other words, the machine learning models learn from past data to make predictions about a patient diagnosis. This research provides a detailed work with the application of planning techniques is used in order to diagnose CVDs. A combination of biological data and medical imaging has been used. Ultimately, as this is a challenging research area open issues and its possible future works have also been discussed.

Original languageEnglish
Title of host publication2020 IEEE 10th International Conference on Intelligent Systems, IS 2020 - Proceedings
EditorsVassil Sgurev, Vladimir Jotsov, Rudolf Kruse, Mincho Hadjiski
PublisherInstitute of Electrical and Electronics Engineers
Pages200-204
Number of pages5
ISBN (Electronic)978-1-7281-5456-5
ISBN (Print)978-1-7281-5457-2
DOIs
Publication statusPublished - 18 Sep 2020
Event10th IEEE International Conference on Intelligent Systems - Sofia, Bulgaria
Duration: 28 Aug 202030 Aug 2020

Publication series

Name2020 IEEE 10th International Conference on Intelligent Systems, IS 2020 - Proceedings
PublisherIEEE
ISSN (Print)1541-1672

Conference

Conference10th IEEE International Conference on Intelligent Systems
Abbreviated titleIS 2020
CountryBulgaria
CitySofia
Period28/08/2030/08/20

Keywords

  • cardiovascular diseases
  • convolutional neural network
  • deep learning
  • U-Net

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